Travel as a risk factor for uncomplicated Plasmodium falciparum malaria in the highlands of western Kenya

Plasmodium falciparum population structure inferred by msp1 amplicon sequencing of parasites collected from febrile patients in Kenya

BACKGROUND

Multiplicity of infection (MOI) is an important measure of Plasmodium falciparum diversity, usually derived from the highly polymorphic genes, such as msp1, msp2 and glurp as well as microsatellites. Conventional methods of deriving MOI lack fine resolution needed to discriminate minor clones. This study used amplicon sequencing (AmpliSeq) of P. falciparum msp1 (Pfmsp1) to measure spatial and temporal genetic diversity of P. falciparum.

METHODS

264 P. falciparum positive blood samples collected from areas of differing malaria endemicities between 2010 and 2019 were used. Pfmsp1 gene was amplified and amplicon libraries sequenced on Illumina MiSeq. Sequences were aligned against a reference sequence (NC_004330.2) and clustered to detect fragment length polymorphism and amino acid variations.

RESULTS

Children < 5 years had higher parasitaemia (median = 23.5 ± 5 SD, p = 0.03) than the > 5-14 (= 25.3 ± 5 SD), and those > 15 (= 25.1 ± 6 SD). Of the alleles detected, 553 (54.5%) were K1, 250 (24.7%) MAD20 and 211 (20.8%) RO33 that grouped into 19 K1 allelic families (108-270 bp), 14 MAD20 (108-216 bp) and one RO33 (153 bp). AmpliSeq revealed nucleotide polymorphisms in alleles that had similar sizes, thus increasing the K1 to 104, 58 for MAD20 and 14 for RO33. By AmpliSeq, the mean MOI was 4.8 (± 0.78, 95% CI) for the malaria endemic Lake Victoria region, 4.4 (± 1.03, 95% CI) for the epidemic prone Kisii Highland and 3.4 (± 0.62, 95% CI) for the seasonal malaria Semi-Arid region. MOI decreased with age: 4.5 (± 0.76, 95% CI) for children < 5 years, compared to 3.9 (± 0.70, 95% CI) for ages 5 to 14 and 2.7 (± 0.90, 95% CI) for those > 15. Females' MOI (4.2 ± 0.66, 95% CI) was not different from males 4.0 (± 0.61, 95% CI). In all regions, the number of alleles were high in the 2014-2015 period, more so in the Lake Victoria and the seasonal transmission arid regions.

CONCLUSION

These findings highlight the added advantages of AmpliSeq in haplotype discrimination and the associated improvement in unravelling complexity of P. falciparum population structure.

Survey and Analysis of Chemoprophylaxis Policies for Domestic Travel in Malaria-Endemic Countries

The prevention of malaria in travelers with the use of antimalarials often occurs in connection with international travel to areas of significant risk of infection. Although these travelers sometimes cause outbreaks in their malaria-free home countries, the cardinal objective of prescribed chemoprophylaxis is to protect the traveler from patent malaria during travel. Here we consider the chemoprophylaxis of domestic travelers from malaria-free but -receptive areas within malaria-endemic countries. The main objective in this setting is the protection of those areas from reintroduced malaria transmission. In order to better understand policy and practices in this regard, we surveyed malaria prevention and treatment guidelines of 36 malaria-endemic countries and 2 that have recently eliminated malaria (Sri Lanka, China) for recommendations regarding malaria chemoprophylaxis for domestic travel. Among them, just 8 provided specific and positive recommendations, 1 recommended without specific guidance, and 4 advised against the practice. Most nations (25/38; 66%) did not mention chemoprophylaxis for domestic travel, though many of those did offer guidance for international travel. The few positive recommendations for domestic travel were dominated by the suppressive prophylaxis options of daily doxycycline or atovaquone-proguanil or weekly mefloquine. The incomplete protection afforded by these strategies, along with impractical dosing in connection with the typically brief domestic travel, may in part explain the broad lack of policies and practices across malaria-endemic nations regarding chemoprophylaxis.

Genetic diversity and population structure of the human malaria parasite Plasmodium falciparum surface protein Pfs47 in isolates from the lowlands in Western Kenya

Plasmodium falciparum parasites have evolved genetic adaptations to overcome immune responses mounted by diverse Anopheles vectors hindering malaria control efforts. Plasmodium falciparum surface protein Pfs47 is critical in the parasite’s survival by manipulating the vector’s immune system hence a promising target for blocking transmission in the mosquito. This study aimed to examine the genetic diversity, haplotype distribution, and population structure of Pfs47 and its implications on malaria infections in endemic lowlands in Western Kenya. Cross-sectional mass blood screening was conducted in malaria endemic regions in the lowlands of Western Kenya: Homa Bay, Kombewa, and Chulaimbo. Dried blood spots and slide smears were simultaneously collected in 2018 and 2019. DNA was extracted using Chelex method from microscopic Plasmodium falciparum positive samples and used to genotype Pfs47 using polymerase chain reaction (PCR) and DNA sequencing. Thirteen observed haplotypes of the Pfs47 gene were circulating in Western Kenya. Population-wise, haplotype diversity ranged from 0.69 to 0.77 and the nucleotide diversity 0.10 to 0.12 across all sites. All the study sites displayed negative Tajima’s D values although not significant. However, the negative and significant Fu’s Fs statistical values were observed across all the study sites, suggesting population expansion or positive selection. Overall genetic differentiation index was not significant (F_ST = -0.00891, P > 0.05) among parasite populations. All Nm values revealed a considerable gene flow in these populations. These results could have important implications for the persistence of high levels of malaria transmission and should be considered when designing potential targeted control interventions.

Challenges and opportunities for use of long-lasting insecticidal nets to prevent malaria during overnight travel in Uganda: a qualitative study

BACKGROUND

Travel is a well-recognized risk factor for malaria. Within sub-Saharan Africa, travellers from areas of lower to higher transmission intensity are potentially at high risk of malaria. Long-lasting insecticidal nets (LLINs) are the primary tool for prevention of malaria, and their widespread use has contributed to substantial reductions in malaria burden. However, travellers often fail to use LLINs. To further explore the challenges and opportunities of using LLINs, travellers were interviewed in Uganda.

METHODS

In August and September 2019, 20 participants attending outpatient clinics at Naguru General Hospital in Kampala with a history of travel out of Kampala within the previous 60 days were purposively selected. Data were collected through in-depth interviews and analysed thematically using NVivo 12.

RESULTS

Of the 20 participants, 13 were male. Thirteen of the 20 participants tested positive for malaria by microscopy, and 5 reported using of LLINs during travel. The main reasons for travel were to attend social events (weddings, funerals, overnight prayers) and for work. travellers who attended social events reported using LLINs less commonly than those who travelled for work. Challenges to using LLINs during travel included: (1) limited access to LLINs; (2) challenges in planning ahead of travel; (3) lack of space or ability to hang LLINs while travelling; (4) impression that LLINs in lodging places were unhygienic; (5) cultural beliefs discouraging use of LLINs during social events; (6) participation in overnight ceremonies; and (7) doubts about efficacy of LLINs. Positive factors influencing use of LLINs during travel included knowledge regarding malaria prevention and good affordability and availability of LLINs.

CONCLUSIONS

Despite good traveller knowledge regarding malaria control measures, use of LLINs was limited. Use of LLINs in the prevention of malaria among travellers from low to high transmission settings needs to be prioritized. This calls for increased behaviour change oriented communication to improve traveller preparedness and consideration of use of repellents in situations where LLINs may not be feasible. The Uganda Ministry of Health and Malaria Control Division should use educational messages to increase awareness about the risks of getting malaria during overnight travel through the media. Truck drivers should be sensitized through their companies to use the available space at the back of the trucks for hanging nets and consider using pop-up nets.

Association between recent overnight travel and use of long-lasting insecticidal nets in rural Uganda: a prospective cohort study in Tororo

Background

The burden of malaria in Uganda remains high, but has become increasingly heterogenous following intensified malaria control. Travel within Uganda is recognized as a risk factor for malaria, but behaviours associated with travel are not well-understood. To address this knowledge gap, malaria-relevant behaviours of cohort participants were assessed during travel and at home in Uganda.

Methods

Residents from 80 randomly selected households in Nagongera sub-county, Tororo district were enrolled into a cohort to study malaria in rural Uganda. All participants were given long-lasting insecticidal nets (LLINs) at enrolment and were evaluated every 4 weeks at the study clinic. Participants were asked if they had travelled overnight from their home, and if so, a questionnaire was administered to capture information on travel details and behaviours. Behaviour while travelling was assessed within 4 weeks following travel during the study clinic visit. Behaviour while at home was assessed using a similar questionnaire during two-weekly home visits. Behaviours while travelling vs at home were compared using log binomial regression models with generalized estimating equations adjusting for repeated measures in the same individual. Analysis of factors associated with LLIN adherence, such as destination and duration of travel, time to bed during travel, gender and age at time of travel, were assessed using log binomial regression models with generalized estimating equations adjusting for repeated measures in the same individual.

Results

Between October 2017 and October 2019, 527 participants were enrolled and assessed for travel. Of these, 123 (23.2%) reported taking 211 overnight trips; 149 (70.6%) trips were within Tororo. Participants were less likely to use LLINs when travelling than when at home (41.0% vs. 56.2%, relative risk [RR] 0.73, 95% CI 0.60–0.89, p = 0.002); this difference was noted for women (38.8% vs 59.2%, RR 0.66, 95% CI 0.52–0.83, p = 0.001) but not men (48.3% vs 46.6%, RR 0.96, 95% CI 0.67–1.40, p = 0.85). In an adjusted analysis, factors associated with LLIN use when travelling included destination (travelling to districts not receiving indoor residual spraying [IRS] 65.8% vs Tororo district 32.2%, RR 1.80, 95% CI 1.31–2.46, p < 0.001) and duration of travel (> 7 nights 60.3% vs one night 24.4%, RR 1.97, 95% CI 1.07–3.64, p = 0.03).

Conclusions

Travellers, particularly women, were less likely to use LLINs when travelling than when at home. LLIN adherence was higher among those who travelled to non-IRS districts and for more than 1 week, suggesting that perceived malaria risk influences LLIN use. Strategies are needed to raise awareness of the importance of using LLINs while travelling.

Travel Is a Key Risk Factor for Malaria Transmission in Pre-Elimination Settings in Sub-Saharan Africa: A Review of the Literature and Meta-Analysis

By sustaining transmission or causing malaria outbreaks, imported malaria undermines malaria elimination efforts. Few studies have examined the impact of travel on malaria epidemiology. We conducted a literature review and meta-analysis of studies investigating travel as a risk factor for malaria infection in sub-Saharan Africa using PubMed. We identified 22 studies and calculated a random-effects meta-analysis pooled odds ratio (OR) of 3.77 (95% CI: 2.49–5.70), indicating that travel is a significant risk factor for malaria infection. Odds ratios were particularly high in urban locations when travel was to rural areas, to more endemic/high transmission areas, and in young children. Although there was substantial heterogeneity in the magnitude of association across the studies, the pooled estimate and directional consistency support travel as an important risk factor for malaria infection.

Risk factors for Plasmodium falciparum infection in the Kenyan Highlands: a cohort study

BACKGROUND

Malaria transmission in African highland areas can be prone to epidemics, with minor fluctuations in temperature or altitude resulting in highly heterogeneous transmission. In the Kenyan Highlands, where malaria prevalence has been increasing, characterising malaria incidence and identifying risk factors for infection is complicated by asymptomatic infection.

METHODS

This all-age cohort study, one element of the Malaria Transmission Consortium, involved monthly follow-up of 3155 residents of the Kisii and Rachuonyo South districts during June 2009-June 2010. Participants were tested for malaria using rapid diagnostic testing at every visit, regardless of symptoms.

RESULTS

The incidence of Plasmodium falciparum infection was 0.2 cases per person, although infections were clustered within individuals and over time, with the majority of infections detected in the last month of the cohort study. Overall, incidence was higher in the Rachuonyo district and infections were detected most frequently in 5-10-year-olds. The majority of infections were asymptomatic (58%). Travel away from the study area was a notable risk factor for infection.

CONCLUSIONS

Identifying risk factors for malaria infection can help to guide targeting of interventions to populations most likely to be exposed to malaria.

Association Between Recent Overnight Travel and Risk of Malaria: A Prospective Cohort Study at 3 Sites in Uganda

Background

Human movement can undermine malaria control efforts. However, understanding of the association between travel and malaria infection in Africa is limited. We evaluated the association between recent overnight travel and malaria incidence in Uganda.

Methods

All children aged 0.5-10 years and 1 adult living in 266 randomly selected households within 3 different regions of Uganda were followed up prospectively. Information on overnight travel was collected in 2015-2016. Malaria, defined as fever with parasites detected by microscopy, was measured using passive surveillance.

Results

At least 1 overnight trip was reported by 64 of 275 (23.3%) participants in Walukuba, 37 of 317 (11.7%) in Nagongera, and 19 of 314 (6.1%) in Kihihi. Among individuals who traveled, the incidence of malaria was higher in the first 60 days after traveling, compared with periods without recent travel at all 3 sites (overall, 1.15 vs 0.33 episodes per person-year; incidence rate ratio, 3.53; 95% confidence interval, 1.85-6.73; P < .001). Risk factors for malaria within 60 days after overnight travel included young age (19.5% in children vs 4.9% in adults; odds ratio, 5.29; 95% confidence interval, 1.34-21.0; P = .02) and not using an insecticide-treated net during travel (18.0% for no use vs 4.1% for any use; 5.10; 1.07-24.5; P = .04).

Conclusions

Recent overnight travel was associated with a higher incidence of malaria. Individuals who travel may represent a high-risk group that could be targeted for malaria control interventions, particularly use of insecticide-treated nets.

Spatial distribution and habitat characterization of mosquito species during the dry season along the Mara River and its tributaries, in Kenya and Tanzania

Background

Vector-borne diseases are increasingly becoming a major health problem among communities living along the major rivers of Africa. Although larger water bodies such as lakes and dams have been extensively researched, rivers and their tributaries have largely been ignored. This study sought to establish the spatial distribution of mosquito species during the dry season and further characterize their habitats along the Mara River and its tributaries.

Methods

In this cross-sectional survey, mosquito larvae were sampled along the Mara River, its two perennial tributaries (Amala and Nyangores), drying streams, and adjacent aquatic habitats (e.g. swamps, puddles that receive direct sunlight [open sunlit puddles], rock pools, hippo and livestock hoof prints, and vegetated pools). Each habitat was dipped 20 times using a standard dipper. Distance between breeding sites and human habitation was determined using global positioning system coordinates. The collected mosquito larvae were identified using standard taxonomic keys. Water physico-chemical parameters were measured in situ using a multiparameter meter. Mean mosquito larvae per habitat type were compared using analysis of variance and chi-square tests, while the relationship between mosquito larvae and physico-chemical parameters was evaluated using a generalized linear mixed model. The Cox-Stuart test was used to detect trends of mosquito larvae distribution. The test allowed for verification of monotonic tendency (rejection of null hypothesis of trend absence) and its variability.

Results

A total of 4001 mosquito larvae were collected, of which 2712 (67.8%) were collected from river/stream edge habitats and 1289 (32.2%) were sampled from aquatic habitats located in the terrestrial ecosystem about 50 m away from the main river/streams. Anopheles gambiae s.s, An. arabiensis, and An. funestus group, the three most potent vectors of malaria in Sub-Saharan Africa, together with other anopheline mosquitoes, were the most dominant mosquito species (70.3%), followed by Culex quinquefasciatus and Cx. pipiens complex combined (29.5%). Drying streams accounted for the highest number of larvae captured compared to the other habitat types. A stronger relationship between mosquito larvae abundance and dissolved oxygen (Z = 7.37, P ≤ 0.001), temperature (Z = 7.65, P ≤ 0.001), turbidity (Z = −5.25, P ≤ 0.001), and distance to the nearest human habitation (Z = 4.57, P ≤ 0.001), was observed.

Conclusions

Presence of malaria and non-malaria mosquito larvae within the Mara River basin calls for immediate action to curtail the insurgence of vector-borne diseases within the basin. A vector control program should be conducted during the dry period, targeting drying streams shown to produce the highest number of larval mosquitoes.

Electronic supplementary material

The online version of this article (10.1186/s40249-017-0385-0) contains supplementary material, which is available to authorized users.

Factors associated with high heterogeneity of malaria at fine spatial scale in the Western Kenyan highlands

Background

The East African highlands are fringe regions between stable and unstable malaria transmission. What factors contribute to the heterogeneity of malaria exposure on different spatial scales within larger foci has not been extensively studied. In a comprehensive, community-based cross-sectional survey an attempt was made to identify factors that drive the macro- and micro epidemiology of malaria in a fringe region using parasitological and serological outcomes.

Methods

A large cross-sectional survey including 17,503 individuals was conducted across all age groups in a 100 km² area in the Western Kenyan highlands of Rachuonyo South district. Households were geo-located and prevalence of malaria parasites and malaria-specific antibodies were determined by PCR and ELISA. Household and individual risk-factors were recorded. Geographical characteristics of the study area were digitally derived using high-resolution satellite images.

Results

Malaria antibody prevalence strongly related to altitude (1350–1600 m, p < 0.001). A strong negative association with increasing altitude and PCR parasite prevalence was found. Parasite carriage was detected at all altitudes and in all age groups; 93.2 % (2481/2663) of malaria infections were apparently asymptomatic. Malaria parasite prevalence was associated with age, bed net use, house construction features, altitude and topographical wetness index. Antibody prevalence was associated with all these factors and distance to the nearest water body.

Conclusion

Altitude was a major driver of malaria transmission in this study area, even across narrow altitude bands. The large proportion of asymptomatic parasite carriers at all altitudes and the age-dependent acquisition of malaria antibodies indicate stable malaria transmission; the strong correlation between current parasite carriage and serological markers of malaria exposure indicate temporal stability of spatially heterogeneous transmission.

The Impact of Hotspot-Targeted Interventions on Malaria Transmission in Rachuonyo South District in the Western Kenyan Highlands: A Cluster-Randomized Controlled Trial

BACKGROUND

Malaria transmission is highly heterogeneous, generating malaria hotspots that can fuel malaria transmission across a wider area. Targeting hotspots may represent an efficacious strategy for reducing malaria transmission. We determined the impact of interventions targeted to serologically defined malaria hotspots on malaria transmission both inside hotspots and in surrounding communities.

METHODS AND FINDINGS

Twenty-seven serologically defined malaria hotspots were detected in a survey conducted from 24 June to 31 July 2011 that included 17,503 individuals from 3,213 compounds in a 100-km2 area in Rachuonyo South District, Kenya. In a cluster-randomized trial from 22 March to 15 April 2012, we randomly allocated five clusters to hotspot-targeted interventions with larviciding, distribution of long-lasting insecticide-treated nets, indoor residual spraying, and focal mass drug administration (2,082 individuals in 432 compounds); five control clusters received malaria control following Kenyan national policy (2,468 individuals in 512 compounds). Our primary outcome measure was parasite prevalence in evaluation zones up to 500 m outside hotspots, determined by nested PCR (nPCR) at baseline and 8 wk (16 June-6 July 2012) and 16 wk (21 August-10 September 2012) post-intervention by technicians blinded to the intervention arm. Secondary outcome measures were parasite prevalence inside hotpots, parasite prevalence in the evaluation zone as a function of distance from the hotspot boundary, Anopheles mosquito density, mosquito breeding site productivity, malaria incidence by passive case detection, and the safety and acceptability of the interventions. Intervention coverage exceeded 87% for all interventions. Hotspot-targeted interventions did not result in a change in nPCR parasite prevalence outside hotspot boundaries (p ≥ 0.187). We observed an average reduction in nPCR parasite prevalence of 10.2% (95% CI -1.3 to 21.7%) inside hotspots 8 wk post-intervention that was statistically significant after adjustment for covariates (p = 0.024), but not 16 wk post-intervention (p = 0.265). We observed no statistically significant trend in the effect of the intervention on nPCR parasite prevalence in the evaluation zone in relation to distance from the hotspot boundary 8 wk (p = 0.27) or 16 wk post-intervention (p = 0.75). Thirty-six patients with clinical malaria confirmed by rapid diagnostic test could be located to intervention or control clusters, with no apparent difference between the study arms. In intervention clusters we caught an average of 1.14 female anophelines inside hotspots and 0.47 in evaluation zones; in control clusters we caught an average of 0.90 female anophelines inside hotspots and 0.50 in evaluation zones, with no apparent difference between study arms. Our trial was not powered to detect subtle effects of hotspot-targeted interventions nor designed to detect effects of interventions over multiple transmission seasons.

CONCLUSIONS

Despite high coverage, the impact of interventions targeting malaria vectors and human infections on nPCR parasite prevalence was modest, transient, and restricted to the targeted hotspot areas. Our findings suggest that transmission may not primarily occur from hotspots to the surrounding areas and that areas with highly heterogeneous but widespread malaria transmission may currently benefit most from an untargeted community-wide approach. Hotspot-targeted approaches may have more validity in settings where human settlement is more nuclear.

TRIAL REGISTRATION

ClinicalTrials.gov NCT01575613.

Genetic variability and population structure of Plasmodium falciparum parasite populations from different malaria ecological regions of Kenya

Transmission intensity, movement of human and vector hosts, biogeographical features, and malaria control measures are some of the important factors that determine Plasmodium falciparum parasite genetic variability and population structure. Kenya has different malaria ecologies which might require different disease intervention methods. Refined parasite population genetic studies are critical for informing malaria control and elimination strategies. This study describes the genetic diversity and population structure of P. falciparum parasites from the different malaria ecological zones in Kenya. Twelve multi-locus microsatellite (MS) loci previously described were genotyped in 225 P. falciparum isolates collected between 2012 and 2013 from five sites; three in lowland endemic regions (Kisumu, Kombewa, and Malindi) and two in highland, epidemic regions (Kisii and Kericho). Parasites from the lowland endemic and highland epidemic regions of western Kenya had high genetic diversity compared to coastal lowland endemic region of Kenya [Malindi]. The Kenyan parasites had a mean genetic differentiation index (FST) of 0.072 (p=0.011). The multi-locus genetic analysis of the 12 MS revealed all the parasites had unique haplotypes. Significant linkage disequilibrium (LD) was observed in all the five parasite populations. Kisumu had the most significant index of association values (0.16; p<0.0001) whereas Kisii had the least significant index of association values (0.03; p<0.0001). Our data suggest high genetic diversity in Kenyan parasite population with the exception of parasite from Malindi where malaria has been on the decline. The presence of significant LD suggests that there is occurrence of inbreeding in the parasite population. Parasite populations from Kisii showed the strongest evidence for epidemic population structure whereas the rest of the regions showed panmixia. Defining the genetic diversity of the parasites in different ecological regions of Kenya after introduction of the artemether-lumefantrine is important in refining the spread of drug resistant strains and malaria transmission for more effective control and eventual elimination of malaria in Kenya.

The effect of intermittent preventive treatment on anti-malarial drug resistance spread in areas with population movement

Background

The use of intermittent preventive treatment in pregnant women (IPTp), children (IPTc) and infant (IPTi) is an increasingly popular preventive strategy aimed at reducing malaria risk in these vulnerable groups. Studies to understand how this preventive intervention can affect the spread of anti-malarial drug resistance are important especially when there is human movement between neighbouring low and high transmission areas. Because the same drug is sometimes utilized for IPTi and for symptomatic malaria treatment, distinguishing their individual roles on accelerating the spread of drug resistant malaria, with or without human movement, may be difficult to isolate experimentally or by analysing data. A theoretical framework, as presented here, is thus relevant as the role of IPTi on accelerating the spread of drug resistance can be isolated in individual populations and when the populations are interconnected and interact.

Methods

A previously published model is expanded to include human movement between neighbouring high and low transmission areas, with focus placed on the malaria parasites. Parasite fitness functions, determined by how many humans the parasites can infect, are used to investigate how fast resistance can spread within the neighbouring communities linked by movement, when the populations are at endemic equilibrium.

Results

Model simulations indicate that population movement results in resistance spreading fastest in high transmission areas, and the more complete the anti-malarial resistance the faster the resistant parasite will tend to spread through a population. Moreover, the demography of infection in low transmission areas tends to change to reflect the demography of high transmission areas. Additionally, when regions are strongly connected the rate of spread of partially resistant parasites (R1) relative to drug sensitive parasites (RS), and fully resistant parasites (R2) relative to partially resistant parasites (R1) tend to behave the same in both populations, as should be expected.

Conclusions

In fighting anti-malarial drug resistance, different drug resistance monitoring and management policies are needed when the area in question is an isolated high or low transmission area, or when it is close and interacting with a neighbouring high or low transmission area, with human movement between them.

Electronic supplementary material

The online version of this article (doi:10.1186/1475-2875-13-428) contains supplementary material, which is available to authorized users.

Testing a multi-malaria-model ensemble against 30 years of data in the Kenyan highlands

Background

Multi-model ensembles could overcome challenges resulting from uncertainties in models’ initial conditions, parameterization and structural imperfections. They could also quantify in a probabilistic way uncertainties in future climatic conditions and their impacts.

Methods

A four-malaria-model ensemble was implemented to assess the impact of long-term changes in climatic conditions on Plasmodium falciparum malaria morbidity observed in Kericho, in the highlands of Western Kenya, over the period 1979–2009. Input data included quality controlled temperature and rainfall records gathered at a nearby weather station over the historical periods 1979–2009 and 1980–2009, respectively. Simulations included models’ sensitivities to changes in sets of parameters and analysis of non-linear changes in the mean duration of host’s infectivity to vectors due to increased resistance to anti-malarial drugs.

Results

The ensemble explained from 32 to 38% of the variance of the observed P. falciparum malaria incidence. Obtained R²-values were above the results achieved with individual model simulation outputs. Up to 18.6% of the variance of malaria incidence could be attributed to the +0.19 to +0.25°C per decade significant long-term linear trend in near-surface air temperatures. On top of this 18.6%, at least 6% of the variance of malaria incidence could be related to the increased resistance to anti-malarial drugs. Ensemble simulations also suggest that climatic conditions have likely been less favourable to malaria transmission in Kericho in recent years.

Conclusions

Long-term changes in climatic conditions and non-linear changes in the mean duration of host’s infectivity are synergistically driving the increasing incidence of P. falciparum malaria in the Kenyan highlands. User-friendly, online-downloadable, open source mathematical tools, such as the one presented here, could improve decision-making processes of local and regional health authorities.

Quantifying cross-border movements and migrations for guiding the strategic planning of malaria control and elimination

Background

Identifying human and malaria parasite movements is important for control planning across all transmission intensities. Imported infections can reintroduce infections into areas previously free of infection, maintain ‘hotspots’ of transmission and import drug resistant strains, challenging national control programmes at a variety of temporal and spatial scales. Recent analyses based on mobile phone usage data have provided valuable insights into population and likely parasite movements within countries, but these data are restricted to sub-national analyses, leaving important cross-border movements neglected.

Methods

National census data were used to analyse and model cross-border migration and movement, using East Africa as an example. ‘Hotspots’ of origin-specific immigrants from neighbouring countries were identified for Kenya, Tanzania and Uganda. Populations of origin-specific migrants were compared to distance from origin country borders and population size at destination, and regression models were developed to quantify and compare differences in migration patterns. Migration data were then combined with existing spatially-referenced malaria data to compare the relative propensity for cross-border malaria movement in the region.

Results

The spatial patterns and processes for immigration were different between each origin and destination country pair. Hotspots of immigration, for example, were concentrated close to origin country borders for most immigrants to Tanzania, but for Kenya, a similar pattern was only seen for Tanzanian and Ugandan immigrants. Regression model fits also differed between specific migrant groups, with some migration patterns more dependent on population size at destination and distance travelled than others. With these differences between immigration patterns and processes, and heterogeneous transmission risk in East Africa and the surrounding region, propensities to import malaria infections also likely show substantial variations.

Conclusion

This was a first attempt to quantify and model cross-border movements relevant to malaria transmission and control. With national census available worldwide, this approach can be translated to construct a cross-border human and malaria movement evidence base for other malaria endemic countries. The outcomes of this study will feed into wider efforts to quantify and model human and malaria movements in endemic regions to facilitate improved intervention planning, resource allocation and collaborative policy decisions.

The demographics of human and malaria movement and migration patterns in East Africa

Introduction

The quantification of parasite movements can provide valuable information for control strategy planning across all transmission intensities. Mobile parasite carrying individuals can instigate transmission in receptive areas, spread drug resistant strains and reduce the effectiveness of control strategies. The identification of mobile demographic groups, their routes of travel and how these movements connect differing transmission zones, potentially enables limited resources for interventions to be efficiently targeted over space, time and populations.

Methods

National population censuses and household surveys provide individual-level migration, travel, and other data relevant for understanding malaria movement patterns. Together with existing spatially referenced malaria data and mathematical models, network analysis techniques were used to quantify the demographics of human and malaria movement patterns in Kenya, Uganda and Tanzania. Movement networks were developed based on connectivity and magnitudes of flow within each country and compared to assess relative differences between regions and demographic groups. Additional malaria-relevant characteristics, such as short-term travel and bed net use, were also examined.

Results

Patterns of human and malaria movements varied between demographic groups, within country regions and between countries. Migration rates were highest in 20–30 year olds in all three countries, but when accounting for malaria prevalence, movements in the 10–20 year age group became more important. Different age and sex groups also exhibited substantial variations in terms of the most likely sources, sinks and routes of migration and malaria movement, as well as risk factors for infection, such as short-term travel and bed net use.

Conclusion

Census and survey data, together with spatially referenced malaria data, GIS and network analysis tools, can be valuable for identifying, mapping and quantifying regional connectivities and the mobility of different demographic groups. Demographically-stratified HPM and malaria movement estimates can provide quantitative evidence to inform the design of more efficient intervention and surveillance strategies that are targeted to specific regions and population groups.

Malaria in East African highlands during the past 30 years: impact of environmental changes

East African highlands are one of the most populated regions in Africa. The population densities in the highlands ranged between 158 persons/km² in Ethiopia and 410 persons/km² in Rwanda. According to the United Nations Population Fund, the region has the world's highest population growth rate. These factors are likely behind the high rates of poverty among the populations. As there were no employment opportunities other than agricultural, this demographic pressure of poor populations have included in an extensive unprecedented land use and land cover changes such as modification of bushland, woodland, and grassland on hillsides to farmland and transformation of papyrus swamps in valley bottoms to dairy pastures and cropland and changing of fallows on hillsides from short or seasonal to longer or perennial. Areas harvested for food crops were therefore increased by more than 100% in most of the highlands. The lost of forest areas, mainly due to subsistence agriculture, between 1990 and 2010 ranged between 8000 ha in Rwanda and 2,838,000 ha in Ethiopia. These unmitigated environmental changes in the highlands led to rise temperature and optimizing the spread and survival of malaria vectors and development of malaria parasites. Malaria in highlands was initially governed by low ambient temperature, trend of malaria transmission was therefore increased and several epidemics were observed in late 1980s and early 2000s. Although, malaria is decreasing through intensified interventions since mid 2000s onwards, these environmental changes might expose population in the highlands of east Africa to an increase risk of malaria and its epidemic particularly if the current interventions are not sustained.

Human movement data for malaria control and elimination strategic planning

Recent increases in funding for malaria control have led to the reduction in transmission in many malaria endemic countries, prompting the national control programmes of 36 malaria endemic countries to set elimination targets. Accounting for human population movement (HPM) in planning for control, elimination and post-elimination surveillance is important, as evidenced by previous elimination attempts that were undermined by the reintroduction of malaria through HPM. Strategic control and elimination planning, therefore, requires quantitative information on HPM patterns and the translation of these into parasite dispersion. HPM patterns and the risk of malaria vary substantially across spatial and temporal scales, demographic and socioeconomic sub-groups, and motivation for travel, so multiple data sets are likely required for quantification of movement. While existing studies based on mobile phone call record data combined with malaria transmission maps have begun to address within-country HPM patterns, other aspects remain poorly quantified despite their importance in accurately gauging malaria movement patterns and building control and detection strategies, such as cross-border HPM, demographic and socioeconomic stratification of HPM patterns, forms of transport, personal malaria protection and other factors that modify malaria risk. A wealth of data exist to aid filling these gaps, which, when combined with spatial data on transport infrastructure, traffic and malaria transmission, can answer relevant questions to guide strategic planning. This review aims to (i) discuss relevant types of HPM across spatial and temporal scales, (ii) document where datasets exist to quantify HPM, (iii) highlight where data gaps remain and (iv) briefly put forward methods for integrating these datasets in a Geographic Information System (GIS) framework for analysing and modelling human population and Plasmodium falciparum malaria infection movements.

Genetic assignment methods for gaining insight into the management of infectious disease by understanding pathogen, vector, and host movement

For many pathogens with environmental stages, or those carried by vectors or intermediate hosts, disease transmission is strongly influenced by pathogen, host, and vector movements across complex landscapes, and thus quantitative measures of movement rate and direction can reveal new opportunities for disease management and intervention. Genetic assignment methods are a set of powerful statistical approaches useful for establishing population membership of individuals. Recent theoretical improvements allow these techniques to be used to cost-effectively estimate the magnitude and direction of key movements in infectious disease systems, revealing important ecological and environmental features that facilitate or limit transmission. Here, we review the theory, statistical framework, and molecular markers that underlie assignment methods, and we critically examine recent applications of assignment tests in infectious disease epidemiology. Research directions that capitalize on use of the techniques are discussed, focusing on key parameters needing study for improved understanding of patterns of disease.

Identifying residual foci of Plasmodium falciparum infections for malaria elimination: the urban context of Khartoum, Sudan

Background

Identifying the location and size of residual foci of infections is critical where malaria elimination is the primary goal. Here the spatial heterogeneity of Plasmodium falciparum infections within the urban extent of Khartoum state in Sudan is investigated using data from cross-sectional surveys undertaken from 1999 to 2008 to inform the Khartoum Malaria Free Initiative (KMFI).

Methods

From 1999–2008 the KMFI undertook cross-sectional surveys of 256 clusters across 203 random samples of residential blocks in the urban Khartoum state in September of each year. Within sampled blocks, at least five persons, including at least one child under the age of five years, were selected from each household. Blood smears were collected from the sampled individuals to examine the presence of P. falciparum parasites. Residential blocks were mapped. Data were analysed for spatial clustering using the Bernoulli model and the significance of clusters were tested using the Kulldorff scan statistic.

Results

A total of 128,510 malaria slide examinations were undertaken during the study period. In 1999, overall prevalence was 2.5%, rising to 3.2% in 2000 and consistently staying below 1% in subsequent years. From 2006, over 90% of all surveyed clusters reported no infections. Spatial clustering of infections was present in each year but not statistically significant in the years 2001, 2002, 2004 and 2008. Spatial clusters of high infection were often located at the junction of the Blue and White Niles.

Conclusion

Persisting foci of malaria infection in Khartoum are likely to distort wide area assessments and disproportionately affect future transmission within the city limits. Improved investments in surveillance that combines both passive and active case detection linked to a geographic information system and a more detailed analysis of the location and stability of foci should be undertaken to facilitate and track malaria elimination in the state of Khartoum.

Environmental, socio-demographic and behavioural determinants of malaria risk in the western Kenyan highlands: a case-control study

OBJECTIVE

To identify risk factors for uncomplicated malaria in highland areas of East Africa at higher risk of malaria epidemics, in order to design appropriate interventions.

METHODS

Prospective, population-based, case-control study in the Nandi Hills, a highland area of western Kenya, to identify environmental, sociodemographic and behavioural factors associated with clinical malaria. Data were collected using field observation, a structured questionnaire, and a global positioning system device.

RESULTS

We interviewed 488 cases of slide-confirmed malaria and 980 age-matched controls. Multivariate analyses associated higher malaria risk with living <250 m of a forest [OR = 3.3 (95% CI 1.5, 7.1)], <250 m of a swamp [2.8 (1.3, 5.9)], <200 m of maize fields [2.0 (1.2, 3.4)], in the absence of trees <200 m [1.6 (1.2, 2.2)], on flat land [1.6 (1.2, 2.2)], in houses without ceilings [1.5 (1.1, 2.2)], in houses with a separate kitchen building [1.8 (1.4, 2.3)] and in households where the female household head had no education [1.9 (1.1, 3.1)]. Travelling out of the study site [2.2 (1.2, 4.1)] was also associated with increased risk. CONCLUSIONS; In this East African highland area, risk of developing uncomplicated malaria was multifactorial with a risk factor profile similar to that in endemic regions. Households within close proximity to forest and swamp borders are at higher risk of malaria and should be included in indoor residual spraying campaigns.

The interaction of seasonal forcing and immunity and the resonance dynamics of malaria

Theory has emphasized the importance of both intrinsic factors such as host immunity and extrinsic drivers such as climate in determining disease dynamics. In particular, seasonality may lead to multi-annual cycles in prevalence, but the likelihood of this depends on the role of acquired immunity. Some diseases including malaria have immunity that falls between the classic susceptible–infectious–removed and susceptible–infectious–susceptible models. Here, we investigate the general conditions promoting the subharmonic resonance behaviour that may lead to multi-annual cycles in a general malaria dynamical model. Utilizing two complementary approaches to bifurcation analyses, we show that resonance is promoted by processes shortening the length of the infectious period and that subharmonic cycles are favoured in situations with strong seasonality in transmission but at intermediate levels of endemicity. We discuss the implications of our results for understanding prevalence patterns in long-term malaria datasets from Kenya that show multi-annual cycles and one from Thailand that does not and discuss the possible implications of treatment.

Genetic structure of Plasmodium falciparum populations between lowland and highland sites and antimalarial drug resistance in Western Kenya

Human travel to malaria endemic lowlands from epidemic highlands has been shown to increase the risk of malaria infections in the highlands. In order to gain insight on the impact of human travel, we examined prevalence, genetic variability and population genetic structure of Plasmodium falciparum in asymptomatic children from one highland site and three surrounding malaria endemic lowland sites in Western Kenya, using multilocus microsatellite genotyping. We further analyzed the frequencies of mutations at the genes conferring resistance to chloroquine and sulfadoxine-pyrimethamine. We found a significant decrease in malaria prevalence in the highland site from 2006 to 2007, 1 year after the introduction of the artemisinin-based combination therapy as first-line treatment for uncomplicated malaria and the scale-up of insecticide-treated bed nets. Population genetic diversity, measured by the number of observed and effective microsatellite alleles and Nei's unbiased genetic diversity, was high and comparable for both highland and lowland populations. Analysis of molecular variance did not detect a significant genetic structure across highland and lowland regions. Similarly, mutations at key antimalarial-resistance codons of the pfcrt, pfmdr1, pfdhfr and pfdhps genes were found at comparable high frequencies in all four sites. High level of gene flow and lack of significant genetic structure in malaria parasites between highland and lowland areas suggest the importance of human travel in shaping parasite population structure.

The Indian Ocean Dipole and malaria risk in the highlands of western Kenya

Epidemics of malaria in the East African highlands in the last 2 decades have often been associated with climate variability, particularly the El Niño-Southern Oscillation (ENSO). However, there are other factors associated with malaria risk and there is increased interest in the influences of the Indian Ocean Dipole (IOD), a climate mode of coupled ocean-atmosphere variability, on East African rainfall. This study explores the relationship between IOD and the number of malaria patients in 7 hospitals from 2 districts in the western Kenyan highlands, controlling for the effects of ENSO. We examined temporal patterns (1982-2001) in the number of malaria cases in relation to the dipole mode index (DMI), defined as the difference in sea surface temperature anomaly between the western (10 degrees S-10 degrees N, 50 degrees-70 degrees E) and eastern (10 degrees S-0 degrees, 90 degrees-110 degrees E) tropical Indian Ocean. We used Poisson regression models, adjusted for ENSO index Niño 3 region (NINO3), seasonal and interannual variations. The number of malaria patients per month increased by 3.4%-17.9% for each 0.1 increase above a DMI threshold (3-4 months lag). Malaria cases increased by 1.4%-10.7% per month, for each 10 mm increase in monthly rainfall (2-3 months lag). In 6 of 7 places, there was no evidence of an association between NINO3 and the number of malaria cases after adjusting for the effect of DMI. This study suggests that the number of malaria cases in the western Kenyan highlands increases with high DMI in the months preceding hospital visits.

Shifting patterns: malaria dynamics and rainfall variability in an African highland

The long-term patterns of malaria in the East African highlands typically involve not only a general upward trend in cases but also a dramatic increase in the size of epidemic outbreaks. The role of climate variability in driving epidemic cycles at interannual time scales remains controversial, in part because it has been seen as conflicting with the alternative explanation of purely endogenous cycles exclusively generated by the nonlinear dynamics of the disease. We analyse a long temporal record of monthly cases from 1970 to 2003 in a highland of western Kenya with both a time-series epidemiological model (time-series susceptible-infected-recovered) and a statistical approach specifically developed for non-stationary patterns. Results show that multiyear cycles of malaria outbreaks appear in the 1980s, concomitant with the timing of a regime shift in the dynamics of cases; the cycles become more pronounced in the 1990s, when the coupling between disease and rainfall is also stronger as the variance of rainfall increased at the frequencies of coupling. Disease dynamics and climate forcing play complementary and interacting roles at different temporal scales. Thus, these mechanisms should not be viewed as alternative and their interaction needs to be integrated in the development of future predictive models.

Assessing the risk of self-diagnosed malaria in urban informal settlements of Nairobi using self-reported morbidity survey

BACKGROUND

Because of the belief that Nairobi is a low risk zone for malaria, little empirical data exists on malaria risk in the area. The aim of this study was to explore the risk of perceived malaria and some associated factors in Nairobi informal settlements using self-reported morbidity survey.

METHODS

The survey was conducted from May to August 2004 on 7,288 individuals in two informal settlements of Nairobi. Participants were asked to report illnesses they experienced in the past 14 days. Logistic regression was used to estimate the odds of perceived-malaria. The model included variables such as site of residence, age, ethnicity and number of reported symptoms.

RESULTS

Participants reported 165 illnesses among which malaria was the leading cause (28.1%). The risk of perceived-malaria was significantly higher in Viwandani compared to Korogocho (OR 1.61, 95%CI: 1.10-2.26). Participants in age group 25-39 years had significantly higher odds of perceived-malaria compared to those under-five years (OR 2.07, 95%CI: 1.43-2.98). The Kikuyu had reduced odds of perceived-malaria compared to other ethnic groups. Individuals with five and more symptoms had higher odds compared to those with no symptoms (OR 23.69, 95%CI: 12.98-43.23).

CONCLUSION

Malaria was the leading cause of illness as perceived by the residents in the two informal settlements. This was rational as the number of reported symptoms was highly associated with the risk of reporting the illness. These results highlight the need for a more comprehensive assessment of malaria epidemiology in Nairobi to be able to offer evidence-based guidance to policy on malaria in Kenya and particularly in Nairobi.

Malaria in Kenya's western highlands

Reemergence of epidemics in tea plantations will likely result in antimalarial-drug resistance.

Records from tea estates in the Kericho district in Kenya show that malaria reemerged in the 1980s. Renewed epidemic activity coincided with the emergence of chloroquine-resistant Plasmodium falciparum malaria and may have been triggered by the failure of antimalarial drugs. Meteorologic changes, population movements, degradation of health services, and changes in Anopheles vector populations are possible contributing factors. The highland malaria epidemics of the 1940s were stopped largely by sporontocidal drugs, and combination chemotherapy has recently limited transmission. Antimalarial drugs can limit the pool of gametocytes available to infect mosquitoes during the brief transmission season.

Low prevalence of Plasmodium falciparum infection among asymptomatic individuals in a highland area of Kenya

In areas of highly seasonal Plasmodium falciparum transmission, the presence of a large reservoir of persistently infected but asymptomatic individuals in the dry season leads to predictable increases in the incidence of clinical malaria in the rainy season. Highland areas, by contrast, are prone to unpredictable epidemics of malaria. To determine the importance of persistent asymptomatic infection in highland areas, we assessed asymptomatic individuals in the highland area of Kipsamoite, Kenya for the presence of P. falciparum blood-stage infection by microscopy and PCR. Five sample collections were performed during rainy and dry seasons over a 31-month period. The final collection was obtained at the start of a rainy season epidemic. Asymptomatic parasitemia was infrequent, ranging from 1.3 to 8.1% by microscopy and 5.9 to 14.5% by PCR testing. Microscopy had low sensitivity (22.2-54.8%) but excellent specificity (95.4-100%) in comparison to PCR testing. Frequency of asymptomatic parasitemia did not differ by age. Gametocyte prevalence was <1% in all periods, except at the start of the epidemic, when it increased to 5.3%. In this epidemic-prone highland area, inter-epidemic periods are characterized by low frequencies of asymptomatically infected individuals. Increases in gametocyte prevalence may be an early indicator of impending outbreaks.